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Remote Machine Learning Jobs in Venice, FL (NOW HIRING)

All JobsMachine Learning JobsRemote Machine Learning JobsRemote Machine Learning Jobs in Venice, FL

Remote Machine Learning information

See Venice, FL salary details

$24K

$40.1K

$82.8K

How much do remote machine learning jobs pay per year?

As of Jul 24, 2026, the average yearly pay for remote machine learning in Venice, FL is $40,079.00, according to ZipRecruiter salary data. Most workers in this role earn between $30,600.00 and $43,300.00 per year, depending on experience, location, and employer.

What engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data modeling, and often working at large tech companies or in specialized industries can earn salaries approaching or exceeding $500,000 annually. Compensation may include base salary, bonuses, and stock options, especially in high-demand markets.

What are the key skills and qualifications needed to thrive as a Remote Machine Learning Engineer, and why are they important?

To thrive as a Remote Machine Learning Engineer, you need a strong background in mathematics, statistics, programming (often Python), and experience with machine learning frameworks, typically supported by a relevant degree. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms (like AWS or GCP), and version control systems is crucial. Strong problem-solving abilities, self-management, and effective virtual communication distinguish top performers in remote settings. These competencies ensure the engineer can build effective models, collaborate across distributed teams, and deliver impactful solutions independently.

How to make 2000 a week working from home?

Remote machine learning professionals can earn $2,000 or more weekly by taking on high-paying freelance projects, consulting roles, or working for companies that offer remote positions with competitive salaries. Building specialized skills in programming, data analysis, and tools like Python, TensorFlow, or cloud platforms can increase earning potential. Consistent work, a strong portfolio, and networking are key to reaching this income level from home.

What Are Remote Machine Learning Jobs?

Machine learning is a method of analyzing data via automating analytical model building. The premise is that systems can learn from data. Machine learning positions include machine learning engineer, computer vision engineer, and senior deep learning engineer. In a remote machine learning job, you work from home in a branch of artificial intelligence performing duties related to computational processing and data. Your goal is to design models that solve business problems, such as helping organizations avoid unknown risks or find profitable opportunities. Your responsibilities include maintaining data pipelines, performing model research and implementation, building machine learning systems, and onboarding new utilities.

What is a remote machine learning job?

A remote machine learning job involves working with algorithms, data, and models to develop predictive systems or automate tasks, all while working from a location outside of a traditional office setting. Professionals in this role use techniques from statistics and computer science to analyze data, train machine learning models, and deploy solutions for real-world applications. Remote machine learning jobs can span various industries, including technology, healthcare, finance, and e-commerce. These roles typically require strong programming skills, knowledge of machine learning frameworks, and the ability to communicate findings effectively with team members or stakeholders. Working remotely offers flexibility, but also requires discipline and self-motivation to succeed.

What are some effective strategies for collaborating with team members while working remotely as a Machine Learning Engineer?

Collaboration in a remote Machine Learning role often relies on clear communication through digital tools such as Slack, Zoom, and project management platforms like Jira or Asana. Regular check-ins and stand-up meetings help keep everyone aligned on project goals and timelines. Sharing code and models via version control systems (like Git) and using collaborative notebooks (such as JupyterHub or Google Colab) are also common practices. Building strong documentation habits and proactively seeking feedback can help ensure smooth teamwork and project success, even across different time zones.

What is the difference between Remote Machine Learning vs Data Scientist?

AspectRemote Machine LearningData Scientist
Required CredentialsBachelor's/Master's in CS, ML certificationsBachelor's/Master's in CS, Statistics, or related field
Work EnvironmentRemote, collaborative teams, tech companiesRemote or on-site, diverse industries, analytics focus
Industry UsageTech, AI startups, researchFinance, healthcare, e-commerce, tech
Search & Comparison IntentOften compared for technical roles in AI/MLBroader data analysis roles, but overlapping skills

Remote Machine Learning specialists focus on developing algorithms and models primarily in tech environments, often requiring advanced programming and ML knowledge. Data Scientists analyze data to extract insights, sometimes utilizing ML techniques. While both roles share skills and credentials, Remote Machine Learning emphasizes model development, whereas Data Scientists focus on data analysis and interpretation.

Are there remote machine learning jobs?

Yes, remote machine learning jobs are widely available across various industries, often requiring skills in programming, data analysis, and familiarity with tools like Python, TensorFlow, or PyTorch. Many companies offer flexible schedules and remote work options for qualified candidates, especially in tech and research sectors.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and deploy AI models, and their role involves understanding algorithms, data preprocessing, and model optimization. While AI automation tools can handle certain tasks, MLEs are essential for creating, fine-tuning, and maintaining complex AI systems, making complete replacement unlikely in the near term.
More about Remote Machine Learning jobs
What are the most commonly searched types of Machine Learning jobs in Venice, FL? The most popular types of Machine Learning jobs in Venice, FL are:
What cities near Venice, FL are hiring for Remote Machine Learning jobs? Cities near Venice, FL with the most Remote Machine Learning job openings:
Remote Machine Learning jobs near you
Infographic showing various Remote Machine Learning job openings in Venice, FL as of July 2026, with employment types broken down into 1% As Needed, 67% Full Time, 29% Part Time, 1% Temporary, and 2% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $40,079 per year, or $19.3 per hour.
Senior Data Engineer ID75059

Senior Data Engineer ID75059

AgileEngine

Port Charlotte, FL • On-site, Remote

$87K - $118K/yr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.
WHY JOIN US
If you\'re looking for a place to grow, make an impact, and work with people who care, we\'d love to meet you!
ABOUT THE ROLE
We are looking for a Senior Data Engineer to design and build scalable data lakes, warehouses, and lakehouse architectures supporting a thematic research platform that processes large volumes of financial data daily. You will implement Python-based ETL/ELT pipelines, orchestrate workflows with Airflow, develop ingestion workflows from third-party APIs, and work with Snowflake, Spark, and AWS to deliver high-performance data infrastructure. The role combines hands-on engineering with technical consulting responsibilities, translating business goals into data architecture roadmaps.
WHAT YOU WILL DO
- Design and implement Python Data Engineering solutions;
- Design and build scalable Data Lakes, Data Warehouses, and Data Lakehouses;
- Design and implement robust ETL/ELT processes at scale using Python, incorporating modern pipeline orchestration tools like Airflow;
- Develop sophisticated ingestion workflows from diverse 3rd party APIs and data sources;
- Manage and optimize various file formats (Parquet, Avro, ORC) and columnar storage to ensure high-performance data retrieval;
- Work with AI development tools to support and accelerate ongoing development, machine learning initiatives and advanced analytics;
- Act as a technical consultant for stakeholders and leadership to gather requirements, understand business goals, and translate them into technical roadmaps;
- Work with Terraform and other tools to build AWS and on-prem infrastructure.
MUST HAVES
- You must be authorized to work for ANY employer in the US (e.g., Green card holders, TN visa holders, GC EAD, H4 EAD, U4U with EAD), as we are unable to sponsor or take over employment visa sponsorship at this time;
- Bachelor’s degree in computer science/engineering or other technical field, or equivalent experience;
- 5+ years of experience with Python (strong, hands-on Python experience is a must);
- 5+ years of experience with data processing, manipulation, and analytics libraries like Pandas, Polars, PySpark or DuckDB;
- 2+ years of experience with Big Data technologies (Spark, Snowflake);
- Expert-level knowledge of pipeline orchestration using Airflow or similar industry-standard tools;
- Deep understanding of Medallion Architecture, columnar file formats, and diverse database technologies (SQL, NoSQL, and Lakehouse architectures);
- Proven ability to work with 3rd party APIs for complex data ingestion tasks;
- Proficiency with modern Cloud platforms (AWS, GCP, Snowflake) and advanced SQL optimization;
- Exceptional soft skills with a proven ability to gather requirements from leadership and collaborate effectively across cross-functional teams;
- Excellence in optimizing complex data pipelines and troubleshooting data latency or consistency issues in massive datasets;
- A self-starter mindset, regularly investigating more efficient data architectures and AI development tools to improve pipeline performance;
- Taking pride in data integrity and the accuracy of the end-to-end pipelines and architectures you build;
- Strong communication skills for seamless global collaboration with stakeholders and distributed teams;
- Upper-intermediate English level.
NICE TO HAVES
- Familiarity with the fintech industry, understanding of financial data, regulatory requirements, and business processes specific to the domain;
- Documentation skills to document data pipelines, architecture designs, and best practices for knowledge sharing and future reference;
- OpenSearch, Elasticsearch;
- AWS Sagemaker Studio, Jupyter for analyze data;
- Terraform;
- Scala.
PERKS AND BENEFITS
- Professional growth: Mentorship, TechTalks, and personalized growth roadmaps.
- Competitive compensation: USD-based pay with education, fitness, and team activity budgets.
- Exciting projects: Modern solutions with Fortune 500 and top product companies.
- Flextime: Flexible schedule with remote and office options.

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